This way, the data is understood or is used for any future marketing campaigns. This type of technique is usually used by many analysts.
Issues relating to security of the information obtained by companies about individual customers. This information is prone to crimes such as hacking creating major security concern for both customers and companies.
Many customer do not give out their information easily because of privacy complains. This way it is not possible to accurately draw relationship or trend in any particular data as the data may be considered incomplete.
Airline companies use data mining techniques to improve their servicing towards customers. The data that is mined to find hidden patterns is about frequent fliers. The issues selected for mining in the frequent flier program are firstly to identify customer characteristics, their most frequent flying zone, class and period of the year in which they usually fly. Secondly, to discover pattern between the sectors based on the activities of the customers. The data mining technique is applied to customer data in three ways: category type, booking type and sector type. Category type revealed that discretionary and invitees were having lower than average use usage whereas members flew more. Booking type disclosed that about 88% of the customers booked their tickets via agents.
Data mining can be used by many different industries. One of the types of industry is the super market industry. Data mining can help them identify customer buying patterns i.e. to place products in such a way that can lead to an increase in the buying behavior of the customer e.g. Wal-Mart’s case of nappies and beer. The other industry that can use data mining is the automobile industry. Customer preferences can be found and all future automobile can be based on aspects usually preferred by customers (e.g. low CO2 emission cars and increased promotion of hybrid cars to control